Predictive Hybrid Modeling

Predictive Hybrid Modeling is a hybrid modeling approach that integrates multiple distinct modeling paradigms or data-driven and physics-based methods to generate accurate predictions of system behavior under varying conditions, distinguished by its explicit focus on predictive accuracy and generalizability in complex, heterogeneous environments.

75

Publications

3K

Citations

297

Authors

168

Institutions

Publications per year

2017–2026

53

Authors

297

  1. ME
    Magdalini Eirinaki

    San Jose State University, United States

    2 publications · 111 citations

    2

    h-index

  2. IJ
    I.S. Jawahir

    University of Kentucky, United States

    2 publications · 100 citations

    2

    h-index

  3. QL
    Qihang Lin

    University of Iowa, United States

    2 publications · 37 citations

    2

    h-index

  4. IP
    Ishmael P. Akaah

    Wayne State University, United States

    2 publications · 29 citations

    2

    h-index

  5. MV
    Michalis Vazirgiannis

    Athens University of Economics and Business, Greece

    2 publications · 111 citations

    2

    h-index

1–5 of 297

Venues

  1. IEEE Access

    4 publications · 168 citations

    4

    h-index

  2. arXiv (Cornell University)

    Repository · 3 publications · 353 citations

    3

    h-index

  3. Scientific Reports

    3 publications · 117 citations

    3

    h-index

  4. Water

    2 publications · 58 citations

    2

    h-index

  5. Expert Systems with Applications

    2 publications · 95 citations

    2

    h-index

1–5